There are two main analysis types, which both work across light modes and plate formats:
CFU detecting models run on each well and use machine learning models which are trained specifically to identify regions of interest on the plate such as a colony growing, a clearing zone forming, or even things like the size of a plantlet as it grows.
Annotations can be turned on in the user interface to understand exactly what a given model is picking up.
Real-time analysis running in the user interface
The CFU detecting model looks at each frame of each plate during the timelapse as illustrated below:
Example of annotations during the timelapse of a single plate
Running at full throughput, each imaging unit can image and analyze 15 petri dishes or 10 microtiter plates (up to 96-well) at a time, allowing for very high throughput automatic quantification.
Example job with 15 triplicate fungal colonies analyzed by a CFU detector model
Plot of the dataset below from the 15-plate job example above
Example of CFU area over time analysis output from a full job with 15 petri dishes
The area of each area identified is one of the most common phenotype metrics, but a variety of other data points are also available including various colorimetric outputs (mean RGB or HSV across the area) and the center coordinate for each area.
Analysis data can be exported in CSV format directly from the analysis export tab.
Analysis export panel with options on analysis model, lighting mode and data format
The color analysis looks at entire wells at once and outputs colorimetric quantifications such as the mean lightness, hue, saturation or RGB color of the well
Blue masks indicate the area analyzed for each well. Orange indicator is shown when hovering the graph on the left to indicate which well corresponds to which line on the graph.
This is very useful especially for multi-well plates as an accurate indicator of growth rates, pH changes or other colorimetric or absorbance-based measurements.
10 6-well plates imaged and analysed by color analysis